Modern precision farming allows farmers to work more efficiently than ever before and spend less money on fertilizers and pesticides. Consumers enjoy lower prices for high quality produce, and farm chemical waste and runoff are reduced. Precision farming encompasses wide-ranging technologies including vehicle control, data management, materials handling and materials application, and environmental sensing. Falling within the broad category of environmental sensing are techniques for monitoring plant growth that help farmers detect problem areas in a field and develop nutrient prescription maps.
Plant growth may be estimated via measurements of normalized difference vegetative index or NDVI. NDVI is derived from optical reflectivity measurements of plants at different wavelengths:
  NDVI  =                    r        NIR            -              r        VIS                            r        NIR            +              r        VIS            
Here, rNIR and rVIS are reflectivity measured at infrared and visible wavelengths, respectively. 780 nm and 660 nm are commonly used NIR and VIS wavelengths, but other wavelengths may be used and other vegetative indices may be defined.
Reflectivity measurements rNIR and rVIS depend on estimating the ratio of reflected and incident light at particular wavelengths. Reflectivity used in computing NDVI may be based on illumination from the sun or illumination from a controlled light source such as a light emitting diode. Sunlight is a convenient, but not consistent, light source. The spectrum of sunlight at the surface of the earth varies with time of day and weather, for instance. NDVI obtained with sunlight illumination may be adequate for relative plant growth assessment, but determining absolute NDVI with sunlight illumination is problematic. Accurate nutrient prescription programs based on NDVI data usually require absolute NDVI measurements.
What are needed are imaging systems and methods for obtaining absolute NDVI data.